AI for Sales Teams: Innovative Ways to Increase Efficiency
Artificial Intelligence (AI) and Machine Learning (ML) are becoming increasingly significant in our progressively digitalised world. Since 2023, more than half of the companies have increased their investments in generative AI.
In sales, they are being used more frequently to optimise business processes, enhance customer experiences, and support sales teams in their daily work. Forecasts indicate that by 2028, about 70% of B2B buyers in the USA will be using AI to optimise their purchasing process. This fundamentally changes the way products and services are researched, evaluated, and selected.
What are Artificial Intelligence and Machine Learning?
Artificial Intelligence (AI) is an area of computer science that focuses on the development of systems capable of mimicking human intelligence. Machine Learning (ML) is a subset of AI, focusing on the development of statistical models and algorithms. These are designed to enable computers to learn autonomously from data and to recognise patterns.
In summary, AI is the overarching concept that describes the imitation of human intelligence, while ML is a method within AI, where systems learn from data to perform specific tasks.
The Use of AI in Sales
Optimising Sales Productivity
By analysing past sales data, data-driven suggestions can be derived to increase productivity within sales. Furthermore, AI can quickly compile individual presentations and informational materials based on existing data and materials. This may include consideration of sales styles, preferences of sales staff, and specific product features or use cases. Additionally, AI can create training, assessments, and onboarding programs for sales staff based on specific guidelines. This leads to better preparation and quicker integration of new team members, ensuring that the entire sales team is always up-to-date.
Increasing Customer Lifetime Value
Predictive AI models are capable of forecasting customer behaviour based on various parameters and optimising sales activities such as personalised offers, cross-selling, upselling, and follow-ups. Sales teams can use AI to create personalised customer brochures and send them with individual links. This enables the provision of tailored solutions that precisely meet the needs of customers. This targeted customer approach can lead to higher customer satisfaction, better customer retention, and thus, increased revenues.
Customised Pricing through Guided Selling
With Guided Selling, customers can answer questions about their needs on their own or in a sales conversation, after which they receive tailored product recommendations. Chatbots can answer the first important customer questions around the clock, providing sales teams with valuable data. Pricing algorithms conduct comprehensive analyses to calculate optimal prices for products and customers. This data-driven pricing takes into account factors such as demand, competitive prices, and customer behaviour, allowing companies to develop competitive and profitable pricing structures.
Competition Analysis
AI tools can analyse the online presence of the competition and direct rivals, gathering valuable information about market dynamics. This includes data on new product launches, price changes, and marketing campaigns. Sales staff can use this data for an upcoming sales conversation, and decision-makers can adjust strategies based on this information to seize new business opportunities and respond to risks in a timely manner.
Information Retrieval from Data Silos
Company data is often stored in various data silos, significantly hindering access to relevant information that could be crucial in customer conversations. AI can be used to analyse and search through these data volumes to instantly access, for example, current prices and information. This ensures that sales staff always have the latest data available and can provide the best advice to their customers.
